Applied Mechanics and Materials Vols. 380-384

Abstract: Retracted paper: Intra-body communication is proposed by Zimmerman in 1995 and the galvanic coupling has been observed to be the best method for data transmission. With the increasing transmission requirements and the development of optical fiber communication, a high speed system is possible to be designed based on the Electro optic methods. In this paper, the characteristics of the intra-body communication system are introduced. Principles and structures of optic modulation for intra-body communication are reviewed. Internal and external modulation methods are introduced and discussed. A system of the electro optic modulation is recommended and discussed.

Abstract: In this paper, a novel method based on Hilbert-Huang transform (HHT) is presented to select optimal timefrequency patterns for single-trial motor imagery electroencephalograph (EEG). The method comprises three progressive steps: 1) employ Empirical Mode Decomposition (EMD) method to decompose EEG signal into a superposition of components or functions called IMFs, and then apply Hilbert transform to the IMFs to calculate the instantaneous frequency and instantaneous amplitude; 2) select the IMFs including the most useful frequency components 3) the optimal timefrequency patterns can be selected according to the instantaneous frequency and instantaneous amplitude of the selected IMFs. After selecting the optimal timefrequency patterns, the features extracted by different methods are classified by Fisher linear discriminator. The results showed that the proposed method could improve the classification accuracy.

Abstract: This paper proposes a face recognition algorithm based on the combination of local binary pattern (LBP) texture features and extreme learning machine (ELM). The face image is divided into several regions, and the LBP features are extracted from these regions and combined together to form a feature vector which will be the input data of ELM. It shows that ELM performs well in classification applications, and ELM and support vector machine (SVM) are equivalent from the optimization point of view. But ELM has milder optimization constraints and much less training time. Our experiments are carried out on two well-known face databases, and the results show that compared with compared to PCA+NN, PCA+SVM and PCA+ELM the proposed method can achieve higher recognition rates.

Abstract: In this paper we studied speech emotion recognition from Mandarin speech signal. Five basic emotion classes and the neutral state are considered. In a listening experiment we verified the speech corpus using a judgment matrix. Acoustic parameters including short-term energy, pitch contour, and formants are extracted from emotional speech signal. Gaussian mixture model is then adopted for training the emotion model. Due to the data challenge in GMM training, we use multiple discriminant analysis for feature optimization and compared with basic Fisher discriminant ratio based method. The experimental results show that using multiple discriminant analysis our GMM classifier gives a promising recognition rate for Mandarin speech emotion recognition.

Abstract: For traditional methods of library identifies based on the two-dimensional code characteristics, these methods are time consuming and a lot of prior experience is required. A method of library identifies based on computer vision technology is proposed. In this method, a preprocessing, such as image equalization, binarization and wavelet change, is first performed on the acquired library label images. Then on the basis of the structural features of the character, the features of library identifiers are obtained by applying PCA for a principal component analysis. A quantum neural network model is designed to have an optimization analysis and calculation on the extracted features, to avoid the drawbacks which need a lot of prior knowledge for the traditional methods. At the same time, an optimization is carried out for the neural network model saving a large amount of computation time. The experimental results show that a recognition rate, up to 98.13%, is obtained by using this method. With a high recognition speed, the method can meet the actual needs to be applied in a practical system.

Abstract: High peak-to-average power ratio (PAPR) is one of the main disadvantages for OFDM signals, which will always result in low power efficiency of power amplifier. The peak cancellation method is a powerful PAPR reduction technique. In this paper, the advanced peak cancellation implement method (APC) is proposed for OFDM signals. Extensive simulations demonstrate that in comparison with the conversational peak cancellation implement method, the APC is more suitable for OFDM signals due to less iteration and comparative performance.

Abstract: Data fitting approach based on test data is commonly adopted on analyzing of thermal effect due to the thruster plume impingement on communication satellites, however, the existing methods are only available for the appendages which are regularly shaped or could be formulated. In this paper, a plume impingement analyzing approach for irregularly shaped appendages is present. The STL (Stereo Lithographic) data is firstly derived from the three-dimensional model of the appendages. Then the STL data are made a kind of interpolation to get small particle size in order to obtain a precise analyzing result. Finally, the normal vector and the location of each triangle grid are obtained from the STL data to form a new model for plume impingement analyzing on irregularly shaped appendages. The new method is proved correct by comparing with PLUME software and the method given in [4].The application range of analyzing exhaust plume impingement on communication satellites can be widely extended by the proposed method.

Abstract: Facial recognition systems often suffer from the problem of "small sample size". Based on the standardization of the LDA algorithm and subsequent improvements, combined with a method of integration using the AdaBoost algorithm, an important value function is added in each iteration process to the difficult elements of the separate sample. Increasing the differences between classifiers improves the separability of the sample in the new feature space, improving the recognition rate to 98.5%. Experiments on the ORL database show that the proposed algorithm is better than traditional one

Abstract: The paper does the pretreating operation of palm print, the process of which includes lowpass filtering, histogram equalization, binarization processing, edge extraction, corner detection, rotating location and extraction of subgraph ROI. In images done with pretreating, translation and rotation phenomenon of noise level has almost been removed, which benefits the characteristic extraction and identification of palm print. And we finally demonstrate by experiments.

Abstract: This paper presents a low power ZigBee sensor network for use in data acquisition fields. The network consists of end devices with sensors, routers that propagate the network over larger distances, and a coordinator that communicates with the computer, which in turns illustrates the data and controls the entire system. The end devices provide data from the sensors to the personal computer, at variable time points determined by the central node. As part of the investigation, extensive studies were performed to reduce the data packets loss. The algorithm developed at the end devices and the coordinator for this purpose is described in detail. Finally, the circuit that drives the humidity sensor, which contributes reducing power consumption and increasing the systems life time, is presented.